Item Response Theory (IRT) models traditionally assume a normal distribution for ability. Although normality is often a reasonable assumption for ability, it is rarely met for observed scores in educational and psychological measurement. Assumptions regarding ability distribution were previously shown to have an effect on IRT parameter estimation. In this study, the normal and uniform distribution prior assumptions for ability were compared for IRT parameter estimation when the actual distribution was either normal or uniform. A simulation study that included a short test with a small sample size and a long test with a large sample size was conducted for this purpose. The results suggested using a uniform distribution prior for ability to achieve more accurate estimates of the ability parameter in the 2PL and 3PL models when the true distribution of ability is not known. For the Rasch model, an explicit pattern that could be used to obtain more accurate item parameter estimates was not found.

中文翻译：

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项目反应理论模型中贝叶斯能力估计的统一先验

传统上，项目响应理论（IRT）模型采用能力的正态分布。虽然常态性通常是对能力的合理假设，但在教育和心理测量中观察到的分数很少能满足。先前已证明有关能力分布的假设会对IRT参数估计产生影响。在这项研究中，当实际分布为正态或均态时，将能力的正态分布和均态分布先验假设进行比较，以进行IRT参数估计。为此，进行了一项模拟研究，其中包括样本量较小的短期测试和样本量较大的长期测试。结果表明，当能力的真实分布未知时，使用先验均匀分布的能力可以更准确地估计2PL和3PL模型中的能力参数。对于Rasch模型，未找到可用于获得更准确的物品参数估计值的显式模式。